Chief Data Scientist

See yourself in our team:

At the heart of the Chief Operations Office, we’re reimagining how we serve customers in operations through the power of transformative AI solutions. 

As a Chief Data Scientist reporting to the AI and Advanced Analytics Lead in COO, you will provide hands-on technical and thought leadership to shape and build the strategic AI roadmap for COO while working across cross-functional squads to design and deliver innovative, responsible, and high impact AI solutions.

You’ll stay at the forefront of emerging technologies, fostering a culture of curiosity, inclusion, and continuous learning in the team, and translating complex ideas into high-impact outcomes for our customers and colleagues. You’ll contribute strongly to guide the team on technically demanding problems across COO as AI continues to evolve.  You will partner across teams and ecosystems to uplift AI capability, embed best practices, and foster a high‑performance AI and Data Science culture.

If you’re passionate about shaping the future of AI while helping others thrive, we’d love you to lead with us.

Key Responsibilities:

• Develop and communicate a strategic vision for AI initiatives, aligning them with organizational goals and driving the overall AI strategy in COO.
• Lead the development of innovative Agentic AI and Gen AI solutions to complex organizational problems, leveraging advanced technical knowledge and specialist expertise.
• Conduct and oversee advanced research to apply new methods and technologies to solve complex problems, ensuring the organisation stays ahead of industry trends.
• Provide strategic and hands-on technical leadership in orchestrating, building and deploying Agentic AI solutions, and ensuring projects are executed with technical excellence and innovation.
• Work closely with other AI and Data Science bar raisers to build a culture of performance and contribute to craft across the entire AI and Data Science Practice.
• Actively partner with internal AI and data science teams and external strategic partners to share knowledge, best practices and bring the best of AI led impact to COO.
• Gen AI and Agentic AI Initiatives: Drive the expansion and adoption of Generative AI and Agentic AI solutions within Operations. Help in reimagining workflows, enhance customer experiences, and simplify internal processes through the design, development, and integration of these AI technologies.
• Enable AI team: Upskill AI and data science practitioners and enhance capabilities in key techniques such as prompt design, RAG, fine-tuning, agentic AI frameworks. Ensure expertise in tools and establish best practices for monitoring, testing, and validating Gen AI solutions.
• Develop Transferrable and Re-usable Frameworks: Collaborate with technology and engineering teams to design and build standardized Gen AI assets applicable across the team

Desired Skills and Experience:

• Leadership and Coordination:
  • Proven experience in leading high-performing multidisciplinary teams with skills spread across Gen AI, Agentic, predictive ML , ML Ops and Data Science.
  • Demonstrated capability in driving reusable Gen AI outcomes that can be leveraged across the group.
  • Proficiency in risk management strategies to identify, mitigate, and manage AI-related risks.
• Technical Skills and Tools:
  • Generative AI Hands-On Delivery Experience: Demonstrated hands-on experience as an Applied Scientist with Machine Learning engineering skills in building and productizing Agentic AI and Generative AI solutions in a business context.
  • Expertise includes: Hands-on coding, prompt engineering, RAG, guardrail design, orchestration design, and familiarity with frameworks like Semantic Kernel and LangGraph.
  • Machine Learning: Expertise in designing and constructing machine learning models, including feature engineering, model selection, hyperparameter tuning, model evaluation, and deployment of predictive models.
  • Tooling Mastery: Hands-on experience in building enterprise level AI agents using Gen AI, traditional ML and data science tools such as LLM, RAG, Spark, Python, R, TensorFlow, PyTorch, SQL, and key AWS integration packages.
  • AI Platforms: Demonstrated experience in developing, deploying, and monitoring Agentic AI, Gen AI and ML models on AWS infrastructure, including Bedrock, Sage Maker, Knowledge Base, and OpenSearch.

Working with us:  

Our people bring their diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace with an ultimate flexibility to work from any of our engineering hubs within Australia. One where we’re driven by our values, and supported to share ideas, initiatives, and energy. One where making a positive impact for customers, communities and each other is part of our every day